Adjustment with solubility parameter

Certain amino-functional actives form water-insoluble complexes with carbomer often this can be prevented by adjusting the solubility parameter of the fluid phase using appropriate alcohols and polyols. 

Carbomers also form pH-dependent complexes with certain polymeric excipients. Adjustment of solubility parameter can also work in this situation. 

The other class of acrylic compatible tackifiers includes those based on ter-penes. Terpenes are monomers obtained by wood extraction or directly from pine tree sap. To make the polyterpene tackifiers, the monomers have to be polymerized under cationic conditions, typically with Lewis acid catalysis. To adjust properties such as solubility parameter and softening point, other materials such as styrene, phenol, limonene (derived from citrus peels), and others may be copolymerized with the terpenes. 

A gradient that runs with 30-80% methanol or acetonitrile is not uncommon. This amount of modifier is generally not needed in supercritical fluid chromatography to affect the same separation. Typical modifier composition in SFC is 1.0-10% and would achieve higher Hildebrand Solubility Parameter adjustment overall than the broader gradients found in LC. 

The only other olefin feedstock which is hydroformylated in an aqueous/organic biphasic system is a mixture of butenes and butanes called raffinate-II [8,61,62]. This low-pressure hydroformylation is very much like the RCH-RP process for the production of butyraldehyde and uses the same catalyst. Since butenes have lower solubility in water than propene, satisfactory reaction rates are obtained only with increased catalyst concentrations. Otherwise the process parameters are similar (Scheme 4.3), so much that hydroformylation of raffinate-11 or propene can even be carried out in the same unit by slight adjustment of operating parameters. 

Values of solubility parameters, their three-dimensional components, and R are available (9,10,12). Not surprisingly, the three-dimensional scheme, with more constants to adjust, does a better job of predicting solubility. 

The solubility parameter for a supercritical fluid, S, increases with increasing density, so it is markedly dependent on pressure. This parameter also depends strongly on temperature, particularly at high pressures. Consequently, the solubility parameter for a fluid can be adjusted through both pressure and temperature. 

SCF carbon dioxide is a lipophilic solvent since the solubility parameter and the dielectric constant are small compared with a number of polar hydrocarbon solvents. Co-solvents(also called entrainers, moditiers, moderators) such as ethanol have been added to fluids such as carbon dioxide to raise the solvent strength while maintaining it s adjustability. Most liquid cosolvents have solubility parameters which are larger than that of carbon dioxide, so that they may be used to increase yields, or to decrease pressure and solvent requirements. A summary of the large increases in solubility that may be obtained with a simple cosolvent is given at the top of Table I. Cosolvents, unlike carbon dioxide, can form electron donor-acceptor complexes (for example hydrogen bonds) with certain polar solutes to influence solubilities and selectivities beyond what would be expected based on volatilities alone. Several thermodynamic models have been developed to correlate and in some cases predict effects of cosolvent on solubilities( ,2). They are used extensively in SCF research and development... 

Fig. lO.a The inset shows the postulated variation of the solubility parameter 8 caused by deuterium labeling (symbols and V correspond to labeled and nonlabeled copolymers, respectively) and due to the change in ethyl ethylene fraction x. The cumulative analysis, described in text, yields the absolute 8 value for deuterated dx (A) and protonated hx (V) copolymers as a function of x at a reference temperature Tref=100 °C determined interaction parameters (as in Fig. 9) allow us to determine two sets of differences AS adjusted here to fit independent PVT data [140,141] measured at 83 °C ( ) and at 121 °C (O). b The interaction parameter, yE/EE, arising from the microstructural difference contribution to the overall effective interaction parameter (hxj/dxpej) in Eq. (19) as a function of the average blend composition (xi+Xj)/2 at a reference temperature of 100 °C.%E/ee values are calculated (see text) from coexistence data ( points correspond to [91,143] and O symbols to [136]) for blend pairs, structurally identical but with swapped labeled component. X marks %e/ee yielded directly [134] for a blend with both components protonated. Solid line is the best fit to data... 

Using this approach we determined [145], independently from assumptions made before Eq. (18b) was used, the relations between the absolute values of 8 for pure random copolymers grouped in two sequences h38-d52-h66-d75-h86-d97 and d38-h52-d66-h75-d86-h97. We adjusted them [145] to fit the best 8 values yielded by PVT properties [140,141] measured at 83 °C ( ) and at 121 °C (O). The concluded absolute values of 8 are presented in Fig. 10a as a function of the composition x for labeled (A) and nonlabeled (V) copolymers (at Tref 100 °C). We see immediately the assumed compositional variation of the solubility parameter. In addition we notice that the absolute value of the 8(x) local slope increases with composition x. This is directly related to the increase with x in pure microstructural interaction parameter %E/EE. 

The UNIQUAC equation has been presented in Section 4.3.3. There are two adjustable equation parameters for each binary. For the binary that is partially miscible, the best way to determine the two binary parameters is to fit the mutual solubility data. For the completely miscible binaries, useful interaction parameters can be obtained from vie data. However, fitting vie data to within experimental accuracy does not uniquely determine the binary parameters. The choice of a particular set of parameters can have a significant effect on the representation of the ternary Ue. The following example has been predicted chloroform-water-acetone at 333°K (using UNIQUAC calculation with binary parameters). Even better results were obtained by fitting the binary parameters of the miscible binaries to ternary lie data. Some examples of good predictions include the following... 

Pressure effects on surfactant systems containing conventional liquid alkanes have not often been studied because of the very low compressibility of liquids. Conflicting results have been reported [38-40]. It is likely that the changes in cohesive energy density (solubility parameter) of the phases over the pressure ranges used were too low to produce definitive trends in phase behavior. The solubility parameter of compressed liquid propane, however, is moderately adjustable with pressure, and therefore a propane-brine-AOT system could be expected to show pressure-driven phase transitions [20,22,41]. 

Fig. 3 Diagram of states for non-ionic block copolymer with soluble A and insoluble B blocks with theoretically predicted stability regions of spherical (S), cylindrical (C), and lamellar (L) aggregates. Values of the theoretical parameters are adjusted for PS-PI copolymer in n-heptane [50]. Different symbols specify morphology of the experimental samples spherical micelles squares), cylindrical micelles triangles), and insoluble aggregates, presumably lamellae diamonds). AFM images of spherical and cylindrical micelles are adopted from [50]...

Tewari et al. [66] determined x foi" some normal, branched, olefinic and aromatic hydrocarbons in n-tetracosane, n-triacontane and n-hexa-triacontane at 355.2 K they calculated the average values in the three solvents and compared them with those given by the theory of regular solutions. The solubility parameter of the solvent, Sj, was dealt with as an adjustable parameter. To ensure the agreement between experimental and calculated values, two values of were required one for aliphatic hydrocarbons (7.73) and one for the aromatic hydrocarbons (6.85). 

It is possible that the experimental conditions necessary to minimize the solubility of the anticipated precipitate induce a new precipitation in addition to the one of interest. For example, the precipitation of Ni + as nickel dimethylglyoximate necessitates working at a slightly basic pH. In these conditions, Fe +, if present, precipitates as ferric hydroxide. These supplementary precipitations may be, in principle, avoided (or at least minimized) by a judicious adjustment of some parameters, in particular the pH value. The supplementary precipitates, which are more insoluble than the anticipated precipitate, may be eliminated by filtration, with the analyte remaining in the filtrate. Another means to overcome this problem is, in a first stage, to mask the parasitic impurity by complexation. The inverse process may also be carried out The analyte may be masked in a first step and the impurity precipitated and filtered off. For example, with a solution containing Cu +, Pb +, Fe +, Co +, andNi + and in order to... 

Considering the emulsification of oil in water, the strategy is to match the hydrophobic and hydrophilic groups of surfactant, respectively, with the oily and continuous aqueous phases. This can be achieved by manipulating the molecular structure of surfactant or by adjusting the composition of one or both phases. When the choice of surfactant is limited, one can adopt the concept of solubility parameter to effectively modify the recipe. As a first approximation, the solubility parameter of a mixture (finux) can be estimated by the following equation ... 

Figures 12.1.22 and 12.1.23 explain technical principles behind formation of efficient and selective membrane. Figure 12.1.22 shows a micrograph of hollow PEI fiber produced from N-methyl-2-pyrrolidone, NMP, which has thin surface layer and uniform pores and Figure 12.1.23 shows the same fiber obtained from a solution in dimethylformamide, DMF, which has a thick surface layer and less uniform pores. The effect depends on the interaction of polar and non-polar components. The compatibility of components was estimated based on their Hansen s solubility parameter difference. The compatibility increases as the solubility parameter difference decreases. Adjusting temperature is another method of control because the Hansen s solubility parameter decreases as the temperature increases. A procedure was developed to determine precipitation values by titration with non-solvent to a cloud point. Use of this procedure aids in selecting a suitable non-solvent for a given polymer/solvent system. Figure 12.1.24 shows the results from this method. Successfid in membrane production by either non-solvent inversion or thermally-induced phase separation requires careful analysis of the compatibilities between polymer and solvent, polymer and non-solvent, and solvent and non-solvent. Also the processing regime, which includes temperature control, removal of volatile components, uniformity of solvent replacement must be carefully controlled.

The solvating power of an SCF resembles that of a liquid. It varies dramatically with variations of pressure and temperature near the critical point. This property is utilized for various separation processes [2,3]. Dielectric constant, solubility parameter, diffusivity, and viscosity can be adjusted simply by changing the reactor pressure or temperature [4]. This will also change enzyme stereoselectivity [5-7]. Without changing solvent and using pressure as the sole adjustable parameter, both enzyme activity and stereoselectivity can be predictably tailored in supercritical environments [8]. 

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